from fastapi import FastAPI, Query
import csv
import os
from threading import Thread
import time
import pandas as pd
import tempfile
from google.cloud import storage
from pydantic import BaseModel

app = FastAPI()

data_location = None
reading_thread = None
stop_reading = False
counter = 1

gcs_bucket_name = "ow-stu-us-ce1-ai-platform"

# process of getting credentials
def get_credentials():
    creds_json_str = os.getenv("BOB") # get json credentials stored as a string
    if creds_json_str is None:
        raise ValueError("GOOGLE_APPLICATION_CREDENTIALS_JSON not found in environment")

    # create a temporary file
    with tempfile.NamedTemporaryFile(mode="w+", delete=False, suffix=".json") as temp:
        temp.write(creds_json_str) # write in json format
        temp_filename = temp.name 

    return temp_filename
    
# pass
os.environ["GOOGLE_APPLICATION_CREDENTIALS"]= get_credentials()

# Ensure the GCS bucket exists
gcs_client = storage.Client()
gcs_bucket = gcs_client.bucket(gcs_bucket_name)

# File path in GCS bucket
gcs_file_path = "deepak_6593/db.csv"

def create_empty_csv():
    # Initialize GCS client
    gcs_client = storage.Client()
    gcs_bucket = gcs_client.bucket(gcs_bucket_name)
    blob = gcs_bucket.blob(gcs_file_path)

    # Define columns for the empty DataFrame
    columns = [
        "timestamp",
        "time",
        "Vibration (mm/s)",
        "Temperature (°C)",
        "Pressure (psi)",
        "Flow Rate (L/min)",
        "Level (%)",
        "Current (A)",
        "Humidity (%)",
        "Oil Quality (%)",
        "pump_status",
        "location"
    ]

    # Create an empty DataFrame with the specified columns
    empty_df = pd.DataFrame(columns=columns)

    # Convert the empty DataFrame to CSV format
    csv_data = empty_df.to_csv(index=False)

    # Delete file if it exists
    if blob.exists():
        blob.delete()

    # Upload the CSV data to the GCS bucket
    blob.upload_from_string(csv_data, content_type="text/csv")

# Create an empty CSV file before endpoint is accessed
create_empty_csv()

def read_csv(location="tambaram"):
    global stop_reading
    global data_location
    global counter
    blob = gcs_bucket.blob(gcs_file_path)
    while not stop_reading:
        file_path = f"https://storage.googleapis.com/dev.openweaver.com/demo/ai/{location}.csv"
        data = pd.read_csv(file_path)
        csv_data = data[0:counter].to_csv(index=False).encode('utf-8')
        blob.upload_from_string(csv_data, content_type='text/csv')
        time.sleep(5)
        counter += 1


def start_reading(location):
    global reading_thread
    reading_thread = Thread(target=read_csv, args=(location,))
    reading_thread.start()

def stop_reading_thread():
    global stop_reading
    global reading_thread
    stop_reading = True
    if reading_thread is not None:
        reading_thread.join()

class LocationRequest(BaseModel):
    location: str

@app.post("/update_location/")
async def update_location(location_request: LocationRequest):
    global reading_thread
    global stop_reading

    location = location_request.location

    if location not in ["tambaram", "velachery"]:
        return {"error": "Invalid location"}

    if reading_thread is not None and reading_thread.is_alive():
        stop_reading_thread()

    stop_reading = False
    start_reading(location)

    return {"message": f"Location updated to {location}"}